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Spatial Econometrics Analysis of Sustainability

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 16687

Special Issue Editors

ISEG – Lisbon School of Economics and Management, Universidade de Lisboa, 1200-781 Lisboa, Portugal
Interests: microeconometrics; spatial econometrics; empirical applications; applied microeconometrics; panel data; semiparametric techniques
Department of Economics, ISCTE-IUL, 1649-026 Lisbon, Portugal
Interests: health economics; applied spatial econometrics; decision under uncertainty
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A spatial perspective has become increasingly relevant to our understanding of sustainability, both on the global scale and at the scale of regions and cities. The Sustainable Development Goals (SDG), which encompass environmental, cultural, economic, social, and health sustainability, have emphasized the importance of geographical analysis. Spatial discrepancies in sustainable development within cities and regions are important subjects and have long been the focus of policy initiatives by national, regional, and local governments.

Furthermore, spatially-referenced data add important contextual and locational information to social, economic, and behavioral sciences, disclosing issues like externalities, interactions, spatial concentration, spatial heterogeneity, and spatial dependence that need to be properly addressed in data analysis and in the specification and estimation of regression models. Techniques to analyze and model spatial data have registered considerable improvements in recent years and simultaneously they have been applied to a wide variety of fields. Spatial econometrics are common in regional science, education, economics, the housing market, natural resources, and healthcare, among others.

This Special Issue aims to bring together innovative empirical research in spatial econometrics and spatial statistics applied to sustainability including studies with spatial data analysis, linear and nonlinear spatial regression models, spatial panels, spatial multilevel modeling, spatial interaction models (gravity models), and spatial nonparametric techniques.

Adopting an interdisciplinary perspective, a broad range of topics on sustainability are expected to be covered, including, but not limited to the following:

  1. Economic growth sustainability
  2. Education sustainability
  3. Energy sustainability
  4. Environment sustainability
  5. Healthcare sustainability
  6. Innovation and knowledge sustainability
  7. Migration sustainability
  8. Trade sustainability

Dr. Isabel Proença
Prof. Dr. Felipa Sampayo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sustainability
  • spatial econometrics
  • sustainable development goals
  • spatial statistics
  • spatial data analysis

Published Papers (7 papers)

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Research

22 pages, 2970 KiB  
Article
Revisiting the Spatial Autoregressive Exponential Model for Counts and Other Nonnegative Variables, with Application to the Knowledge Production Function
by Isabel Proença and Ludgero Glórias
Sustainability 2021, 13(5), 2843; https://0-doi-org.brum.beds.ac.uk/10.3390/su13052843 - 05 Mar 2021
Cited by 3 | Viewed by 1661
Abstract
This paper proposes a two-step pseudo-maximum likelihood estimator of a spatial autoregressive exponential model for counts and other nonnegative variables; it is particularly useful for dealing with zeros. It considers a model specification allowing us to easily determine the direct and indirect partial [...] Read more.
This paper proposes a two-step pseudo-maximum likelihood estimator of a spatial autoregressive exponential model for counts and other nonnegative variables; it is particularly useful for dealing with zeros. It considers a model specification allowing us to easily determine the direct and indirect partial effects of explanatory variables (spatial spillovers and externalities). A simulation study shows that this method generally behaves better in terms of bias and root mean square error than existing procedures. An empirical example estimating a knowledge production function for the NUTS II European regions is analyzed. Results show that there is spatial dependence between regions on the creation of innovation, where regions less able to transform R&D expenses into innovation benefit from knowledge spatial spillovers through indirect effects. It is also concluded that the socioeconomic environment is important and that, unlike public R&D institutions, private companies are efficient at knowledge production. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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17 pages, 3179 KiB  
Article
Effect of Hierarchical Parish System on Portuguese Housing Rents
by Sofia Vale and Felipa de Mello-Sampayo
Sustainability 2021, 13(2), 455; https://0-doi-org.brum.beds.ac.uk/10.3390/su13020455 - 06 Jan 2021
Cited by 2 | Viewed by 1994
Abstract
This manuscript analyzes an inter-parish housing rents gradient with respect to surrounding parishes. Using data on housing rents for 4049 Portuguese parishes in 278 municipalities, the paper explores the spatial patterns of housing rents using the geographically weighted regression (GWR) methodology. The housing [...] Read more.
This manuscript analyzes an inter-parish housing rents gradient with respect to surrounding parishes. Using data on housing rents for 4049 Portuguese parishes in 278 municipalities, the paper explores the spatial patterns of housing rents using the geographically weighted regression (GWR) methodology. The housing rents can be explained by socio-economic factors comprising the effects of unemployment, sustainability, social diversity, elderly dependency, and population density. The proportion of overcrowded dwellings reflecting how poor living conditions affect housing rents was also included in the spatial analysis. On the structural side, characteristics of the dwellings were also included such as the area of the home and the number of other homes available in the parishes. Locational factors reflect households’ valuation for access to other parishes. In order to capture location characteristics, besides considering mobility within municipalities, the GWR allowed using distances to nearby parishes, i.e., parish hierarchy distance effect. The results suggest that the Portuguese rental housing market exhibits a heterogeneous pattern across the territory, displaying spatial variability and a hierarchical space pattern as a consequence of its locational attributes. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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25 pages, 2086 KiB  
Article
Environmental Concern and Urbanization in India: Towards Psychological Complexity
by Johannes Bettin and Meike Wollni
Sustainability 2020, 12(24), 10402; https://0-doi-org.brum.beds.ac.uk/10.3390/su122410402 - 12 Dec 2020
Cited by 1 | Viewed by 1944
Abstract
Urbanizing social-ecological systems often experience environmental degradation, especially in the Global South. Traditional urban psychology has attributed this to decreasing environmental concern due to weakening connections to nature. However, urban psychological research has barely considered how predictions may improve when including psychological complexity, [...] Read more.
Urbanizing social-ecological systems often experience environmental degradation, especially in the Global South. Traditional urban psychology has attributed this to decreasing environmental concern due to weakening connections to nature. However, urban psychological research has barely considered how predictions may improve when including psychological complexity, exemplified by context, in the urbanization-concern link. In this work, we test for sensitivity of a loss of nature connection to cultural context, for substitution by additional southern urban features, and for the emergence of aggregate preferences based on the feedback between these mediators in regard to the overall relationship. Our structural equations model is calibrated using original survey data from the globalized southern megacity Bangalore, India. The spatial explicitness of our data allows for representative sampling from its rich urban variation. Spatial lags of exogenous variables provide instrumental variables to control for endogeneity arising from feedback. The results suggest that modernization-induced value change is the main policy leverage that facilitates pro-environmental preferences within a uniquely Indian interplay of various urban psychological effects. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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25 pages, 11553 KiB  
Article
Regionally Divergent Patterns in Factors Affecting Municipal Waste Production: The Polish Perspective
by Elżbieta Antczak
Sustainability 2020, 12(17), 6885; https://0-doi-org.brum.beds.ac.uk/10.3390/su12176885 - 24 Aug 2020
Cited by 9 | Viewed by 2187
Abstract
This article attempts to identify factors impacting on the quantity of municipal waste in Polish 2478 communes (LAU-2), taking into account the variability of particular determinants’ influence depending on their regional diversification. The analysis covers the years 2005–2018. The dependent variable is the [...] Read more.
This article attempts to identify factors impacting on the quantity of municipal waste in Polish 2478 communes (LAU-2), taking into account the variability of particular determinants’ influence depending on their regional diversification. The analysis covers the years 2005–2018. The dependent variable is the volume of municipal waste in kg per capita, whereas the group of determinants include: economic and human development, uncontrolled dumping sites, population density, population at the working age, migration, tourism, urbanization, dwellings and housing, retail sales, entities, education, and investments in waste management. The geographically weighted regression with spatial error term (GWR–SEM) was employed in this study. The model enabled not only the specification of the waste production determinants, but also the analysis of the variability in the strength and direction of dependencies occurring between the examined variables in individual communes. The results proved that the higher the level of education, the less waste is generated (in north-central Poland); the business entities and working-age population are crucial for the waste quantity in communes of eastern Poland; the factors most important to regional range affecting the waste quantity are urban and business development, and most important to strength are higher education and the share of working-age individuals. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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19 pages, 646 KiB  
Article
Spatial Interaction Model for Healthcare Accessibility: What Scale Has to Do with It
by Felipa de Mello-Sampayo
Sustainability 2020, 12(10), 4324; https://0-doi-org.brum.beds.ac.uk/10.3390/su12104324 - 25 May 2020
Cited by 7 | Viewed by 2634
Abstract
This manuscript develops a theoretical spatial interaction model using the entropy approach to relax the assumption of the deterministic utility function. The spatial healthcare accessibility improves as the demand for healthcare increases or the opportunity cost of traveling to and from healthcare providers [...] Read more.
This manuscript develops a theoretical spatial interaction model using the entropy approach to relax the assumption of the deterministic utility function. The spatial healthcare accessibility improves as the demand for healthcare increases or the opportunity cost of traveling to and from healthcare providers decreases. The empirical application used different spatial econometric techniques and multilevel modeling to evaluate the spatial distribution of existing hospitals in Texas and their social and economic correlates. To control for spatial autocorrelation, spatial autoregressive regression models were estimated, and geographically weighted regression models examined potential spatial non-stationarity. The multilevel modeling controlled for spatial autocorrelation and also allowed local variation and spatial non-stationarity. The empirical analysis showed that healthcare accessibility was not stationary in Texas in 2015, with areas of poor accessibility in rural and peripheral areas in Texas, when using hospitals’ location and county data. The model of spatial interaction applied to healthcare accessibility can be used to evaluate policies aiming at the provision of health services, such as closures of hospitals and capacity increases. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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14 pages, 1694 KiB  
Article
Nonlinear Effects of Human Capital and R&D on TFP: Evidence from European Regions
by Arkadiusz Kijek and Tomasz Kijek
Sustainability 2020, 12(5), 1808; https://0-doi-org.brum.beds.ac.uk/10.3390/su12051808 - 28 Feb 2020
Cited by 8 | Viewed by 2597
Abstract
The aim of the paper is to study the impact of human capital and R&D on Total Factor Productivity (TFP) from a nonlinear perspective. In the spirit of the theory of innovation-driven growth and models with thresholds in human capital and low-growth equilibria, [...] Read more.
The aim of the paper is to study the impact of human capital and R&D on Total Factor Productivity (TFP) from a nonlinear perspective. In the spirit of the theory of innovation-driven growth and models with thresholds in human capital and low-growth equilibria, we hypothesize that the impact of human capital and R&D on TFP is nonlinear. We also make an attempt to explain complementarities between R&D expenditures and human capital, applying developments in the R&D-based growth models. We use spatial panel data models to estimate the link among R&D, human capital, and TFP across the European regions between 2009 and 2014. Empirical evidence shows that there are decreasing returns to human capital and R&D in the European regional space. Moreover, R&D and human capital turn out to be strategic complements. Finally, regional TFP is found to be positively affected by TFP of neighboring regions. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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19 pages, 553 KiB  
Article
Science and Technology Resource Allocation, Spatial Association, and Regional Innovation
by Fuqin Zhang, Yue Wang and Wei Liu
Sustainability 2020, 12(2), 694; https://0-doi-org.brum.beds.ac.uk/10.3390/su12020694 - 17 Jan 2020
Cited by 12 | Viewed by 2593
Abstract
Considering the impact of science and technology resource allocation on regional innovation output, based on the inter-provincial panel data of 30 provinces in China from 1998 to 2017, this paper establishes a regional innovation output growth model, including science and technology resource input [...] Read more.
Considering the impact of science and technology resource allocation on regional innovation output, based on the inter-provincial panel data of 30 provinces in China from 1998 to 2017, this paper establishes a regional innovation output growth model, including science and technology resource input and science and technology resource allocation, and investigates the spatial relationship between regional innovation output and the allocation of science and technology resources, the effect of the inter-subjective configuration structure and inter-regional space re-allocation on regional innovation output. The research results show that there are obvious spatial autocorrelation agglomeration characteristics of China’s regional innovation output and science and technology resource input. The efficiency of the allocation of science and technology resources in the region is relatively low. The application-oriented research subjects with enterprise-oriented research are more efficient in investing in science and technology resources, and the promotion of regional innovation output is more significant. The investment in science and technology resources in neighboring provinces will have a significant inhibitory effect on the province’s innovation output. The regional mobility of science and technology resources has a significant role in promoting regional innovation output growth. The effect of science and technology personnel mobility on regional innovation output is better than that of technology capital flows. Full article
(This article belongs to the Special Issue Spatial Econometrics Analysis of Sustainability)
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